Evaluation of location’s attractiveness for business growth in smart development
Bibliographic Data
| ID | 15067829 |
|---|---|
| Authors | Vytautas Snieška (0000-0001-8777-273X, Kaunas University of Technology, corresponding author), Ineta Zykiene (0000-0003-2138-7948, Kaunas University of Technology), Daiva Burksaitiene (0000-0002-2898-596X, Vilnius Gediminas Technical University, Lithuania) |
| Year | 2019 |
| Volume | 32 |
| Issue | 1 |
| Pages | 925-946 |
| Publication date | 2019-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Economic Research-Ekonomska Istraživanja (JOURNAL) |
| Journal identifiers | ISSN: 1331-677X • E-ISSN: 1848-9664 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/1331677x.2019.1590217 |
| OpenAlex | W2944535907 |
| Language | EN |
| Citations received | 2 |
| References cited | 67 |
The issue of a location's attractiveness for business development in literature lacks approach, when attractiveness is assessed not as a set of factors which determine individual attractiveness, but as a locality's ability to attract, maintain, and create business and investments. The contribution of the research to the discipline is a multi-criterion model of factors determining the location’s attractiveness for business development in the context of smart growth, as a methodological tool to evaluate and analyse the scientific problem in a question which is proposed by us. The attractiveness of a location for business development in the model is combined with the concept of smart development. A new and reliable instrument for decision-makers and managers is presented. An example of panel data analysis of 36 indicators and 3600 observations from 10 cross-sections of annual data for determining the role of quantitative indicators in attractiveness index is provided and timing lags influence is assessed. The method proposed is suitable for the attractiveness analysis of any location if the necessary data is available
Attractiveness · Business · Geography · Process management · Computer Science · Psychology · Regional Socio-Economic Development Trends · Smart Cities and Technologies · Socioeconomic and Demographic Analysis · Marketing
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| Citations per year | 0.33 |
|---|---|
| Citation span | 2020 - 2021 (2) |
| Highly cited | No |